Evidence map›Paper›PMID 36248944›Full record

ArticleComputational intelligence and neuroscience2022

Intelligent Evaluation Algorithm of English Writing Based on Semantic Analysis.

Jing Wang, Bin Liu

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jing WangSchool of Foreign Studies, Suqian University, Suqian 223800, Jiangsu, China.ORCID https://orcid.org/0000-0002-1452-5735
Bin LiuSchool of Foreign Studies, Suqian University, Suqian 223800, Jiangsu, China.ORCID https://orcid.org/0000-0002-4242-8692

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to solve the intelligent evaluation of English writing, this paper proposes a method based on the English semantic neural network algorithm. This paper first briefly analyzes the research background of the English semantic analysis system, then expounds on the relevant technologies of the English distance similarity algorithm, semantic analysis intelligent algorithm structure, word analysis algorithm, sentence part of speech analysis algorithm, sentence semantic analysis algorithm, and neural network algorithm, and finally expounds the database and method implementation of the English semantic analysis system, so as to provide guarantee for the design of the English semantic analysis system. The experimental results show that the recognition accuracy of the BRF network for English characters can reach 96.35%, which is 7.79% higher than that of the BP network; the AUC of the BRF network reaches 0.89, which is closer to 1 compared with 0.72 of the BP network. The test results are in good agreement with the antinoise curve test results of the figure. It is proved that the English semantic neural network algorithm can effectively improve the accuracy of English translation and further improve the efficiency of the system.

Indexed as

LanguageSemanticsAlgorithmsNeural Networks, ComputerWriting

Identifiers

PMID36248944
PMCPMC9556217

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.